PROJECT SUMMARY/ABSTRACT African American men (AAM) disproportionately experience the burden of prostate cancer with a mortality rate approximately 2.4-fold greater than that observed among white U.S. men. This represents the single largest known cancer disparity by race in the U.S., and it may reflect both biologic heterogeneity in the cancers that arise in AAM, as well as differences in socioeconomic factors that influence healthcare utilization. The relative contribution of sociocontextual and biologic factors to prostate cancer disparities remains unclear. Prostate cancers are phenotypically and molecularly heterogeneous. A better understanding of tumor subtypes by race may aid in the understanding of disease etiology and disparities. The identification of intrinsic subtypes in other cancers, such as breast cancer, has had profound implications for our understanding of the underlying biology and clinical management of those cancers. We will leverage transcriptomic and clinical data from the Men of African Descent and Carcinoma of the Prostate Network and GenomeDx Decipher Genomic Resource Information Database? to investigate molecular tumor subtypes with respect to prostate cancer disparities. We hypothesize that the clinical management of prostate cancer can be further optimized for AAM if we can improve the understanding of tumor heterogeneity. To evaluate race- specific differences in tumor molecular prostate cancer subtypes, we propose the following. First, we will characterize the PAM50 subtypes prostate cancer in AAM and white men with prostate cancer. We will evaluate the distribution of PAM50 subtypes by self-identified race/ethnicity (SIRE), their associations with established prognostic factors, and whether they predict differential prognosis by SIRE. Second, we will derive novel molecular subtypes for prostate cancer in AAM. To that end, we will perform consensus clustering analysis to identify and validate molecular subtypes in AAM, develop a gene set predictor of AA prostate cancer subtypes, and assess whether the novel subtypes are differentially associated with prognostic markers or predict differential prognosis by SIRE. Finally, we propose to apply causal mediation analysis to determine the extent to which observed disparities in prostate cancer outcomes can be attributed to differences in subtype prevalence and other prognostic factors by SIRE. These research aims are supported by a comprehensive training plan tailored to my training goals: developing an applied knowledge of advanced concepts in prostate cancer biology, epidemiology, and disparities, and developing a bioinformatic and computational biology skillset. With the support of my Sponsor and Advisory Panel and the rich training environment of Dana-Farber Cancer Institute, this award will help facilitate my transition to research independence.